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Design and realization of a remote monitoring and diagnosis and prediction system for large rotating

Shaohong WANG, Tao CHEN, Jianghong SUN

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 165-170 doi: 10.1007/s11465-009-0090-1

Abstract: The designed remote monitoring and diagnosis and prediction system for large rotating machinery integratesThe system can make further implementation of equipment prediction technology research based on conditionThe system monitors real-time condition of the equipment and achieves early fault prediction with great

Keywords： large rotating machinery     remote monitoring     fault diagnosis     prediction system    

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Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Frontiers in Energy 2013, Volume 7, Issue 4,   Pages 468-478 doi: 10.1007/s11708-013-0282-6

Abstract: by using artificial neural network (ANN) with the objective to minimize the overall system cost of theUnder-prediction or over-prediction will result in an unnecessary commitment of generating units or buyingTherefore, an accurate frequency prediction is the first step toward optimal GS.The proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu, which reduces the overall system cost of the state utility by keeping off the dearer units selected

Keywords： artificial neural network (ANN)     frequency prediction     availability-based tariff (ABT)     generation scheduling    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainabilityThis study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionaryANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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The Development of the Operational System for Meteorological Prediction in China

Yan Hong,Li Zechun,Ma Qingyun,Tian Cuiying

Strategic Study of CAE 2000, Volume 2, Issue 11,   Pages 88-93

Abstract:

In This article the progress of the operational system for meteorological prediction in China wereIn particular, the major R & D achievements in NWP operational system are summarized.Finally, the outlook of future meteorological prediction systems in the 21st century are addressed briefly

Keywords： meteorological prediction     operational system     development    

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Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

Frontiers in Energy 2007, Volume 1, Issue 1,   Pages 113-119 doi: 10.1007/s11708-007-0013-y

Abstract: In accordance with the new near-zero emission coal utilization system with combined gasification andBased on these calculations, the whole system efficiency calculation method that complies with the massTo enhance the system efficiency, the system pressure and the gasifier carbon conversion ratio were optimizedThe results indicate that the system efficiency increases with increasing pressure and gasifier carbonThe system efficiency could reach around 62.1% when operated in these two optimum parameters.

Keywords： influence     efficiency calculation     optimum     software FactSage     transport    

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A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Pengfei DU, Zhiyi LI, Jinliang HUANG

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 5,   Pages 735-745 doi: 10.1007/s11783-013-0560-x

Abstract: This paper introduces a drinking water source simulation and prediction system that consists of a watershedThis system provides methods and technical guidance for the conventional management of water sourcesIn this study, the sub-models of the system were developed based on the data of the Jiangdong Reservoirwere integrated by computer programming, and the watershed model was indirectly integrated into the systemFurthermore, three applications for Jiangdong Reservoir water protection utilizing the system were introduced

Keywords： water source     integrated modeling system     prediction     Jiulong River    

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A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

Frontiers in Energy 2014, Volume 8, Issue 4,   Pages 480-489 doi: 10.1007/s11708-014-0334-6

Abstract: This paper focuses on modeling and performance predetermination of a photovoltaic (PV) system with aThis control scheme appropriately chooses the optimum operating point of the system, ensuring long-termThe numerical simulation of the system is performed in Matlab/Simulink and is validated with experimentalThe operation of the system with the proposed control scheme is verified by varying the irradiation levels

Keywords： photovoltaic system     boost converter     maximum power point tracking (MPPT)     DC permanent-magnet motor     centrifugal    

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Study on Reliability Prediction and Simulation for Mechanical System Undergoing Maintenance

Huang Liangpei,Yin Xiyun and Yue Wenhui

Strategic Study of CAE 2007, Volume 9, Issue 12,   Pages 69-74

Abstract: equipment is broken, so it is necessary to research and estimate the safety reliability of mechanical systemBased on the timetofailure density function of parts, the mechanical system reliability model is constructedBy means of simulation of the system reliability model, concerned parameters with mechanical systems

Keywords： reassembly and maintenance     reliability prediction     age distribution     failure rate    

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Construction risks of Huaying mount tunnel and countermeasures

Haibo YAO, Feng GAO, Shigang YU, Wei DANG

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 3,   Pages 279-285 doi: 10.1007/s11709-017-0414-x

Abstract: One is geology prediction, and the other is automatic wireless real-time monitoring system, which contains

Keywords： prediction     automatic?monitoring?system    

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

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Position-varying surface roughness prediction method considering compensated acceleration in milling

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 855-867 doi: 10.1007/s11465-021-0649-z

Abstract: Surface roughness will be affected by system position dependent vibration even under constant parameterAiming at surface roughness prediction in the machining process, this paper proposes a position-varyingsurface roughness prediction method based on compensated acceleration by using regression analysis.i>R-square proving the effectiveness of the filtering features, is selected as the input of the predictionMoreover, the prediction curve matches and agrees well with the actual surface state, which verifies

Keywords： surface roughness prediction     compensated acceleration     milling     thin-walled workpiece    

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Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0961-2

Abstract: Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

Keywords： pile responses     excavation     prediction     deflection     bending moments    

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Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 479-488 doi: 10.1007/s11708-016-0425-7

Abstract: In this paper a novel method for reliability prediction and validation of nuclear power units in serviceThe accuracy of the reliability prediction can be evaluated according to the comparison between the predictedFurthermore, the reliability prediction method is validated using the nuclear power units in North American

Keywords： nuclear power units in service     reliability     reliability prediction     equivalent availability factors    

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Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 171-175 doi: 10.1007/s11465-009-0091-0

Abstract: Trend prediction technology is the key technology to achieve condition-based maintenance of mechanicalTo ensure the normal operation of units and save maintenance costs, trend prediction technology is studiedThe main methods of the technology are given, the trend prediction method based on neural network isput forward, and the expert system based on the knowledge is developed.The industrial site verification shows that the proposed trend prediction technology can reflect the

Keywords： water injection units     condition-based maintenance     trend prediction    

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Title Author Date Type Operation

Design and realization of a remote monitoring and diagnosis and prediction system for large rotating

Shaohong WANG, Tao CHEN, Jianghong SUN

Journal Article

Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Journal Article

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

The Development of the Operational System for Meteorological Prediction in China

Yan Hong,Li Zechun,Ma Qingyun,Tian Cuiying

Journal Article

Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

Journal Article

A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Pengfei DU, Zhiyi LI, Jinliang HUANG

Journal Article

A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

Journal Article

Study on Reliability Prediction and Simulation for Mechanical System Undergoing Maintenance

Huang Liangpei,Yin Xiyun and Yue Wenhui

Journal Article

Construction risks of Huaying mount tunnel and countermeasures

Haibo YAO, Feng GAO, Shigang YU, Wei DANG

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Position-varying surface roughness prediction method considering compensated acceleration in milling

Journal Article

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Journal Article

Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Journal Article

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Journal Article